MLPerf Storage v1.0 Benchmark Results Reveal Performance Scores of Systems for AI Training
Techstrong.ai, Tuesday, February 18th, 2025
As artificial intelligence (AI) models grow more powerful, enterprises increasingly find their storage solutions unable to handle the data load - or bring data fast enough to the processors.
In 2022, Meta reported its infrastructure growth trends from the previous two years. According to the data, Meta's AI infrastructure requirements had grown in leaps and bounds - principally driven by increases in the scale of data used to train its AI models. The growth, the report stated, was between 1.75 to 2x. Side by side, Meta's data ingestion throughput requirement too had jumped up 3 to 4 times.
The MLPerf Storage benchmark, David Kanter, executive director of MLCommons, a non-profit AI safety work group that tests AI systems-under-tests, said, was born out of this trend.